def test_get_peak():
"""Test peak getter."""
evoked = read_evokeds(fname, condition=0, proj=True)
pytest.raises(ValueError, evoked.get_peak, ch_type='mag', tmin=1)
pytest.raises(ValueError, evoked.get_peak, ch_type='mag', tmax=0.9)
pytest.raises(ValueError,
evoked.get_peak,
ch_type='mag',
tmin=0.02,
tmax=0.01)
pytest.raises(ValueError, evoked.get_peak, ch_type='mag', mode='foo')
pytest.raises(RuntimeError, evoked.get_peak, ch_type=None, mode='foo')
pytest.raises(ValueError, evoked.get_peak, ch_type='misc', mode='foo')
ch_name, time_idx = evoked.get_peak(ch_type='mag')
assert (ch_name in evoked.ch_names)
assert (time_idx in evoked.times)
ch_name, time_idx, max_amp = evoked.get_peak(ch_type='mag',
time_as_index=True,
return_amplitude=True)
assert (time_idx < len(evoked.times))
assert_equal(ch_name, 'MEG 1421')
assert_allclose(max_amp, 7.17057e-13, rtol=1e-5)
pytest.raises(ValueError, evoked.get_peak, ch_type='mag', merge_grads=True)
ch_name, time_idx = evoked.get_peak(ch_type='grad', merge_grads=True)
assert_equal(ch_name, 'MEG 244X')
data = np.array([[0., 1., 2.], [0., -3., 0]])
times = np.array([.1, .2, .3])
ch_idx, time_idx, max_amp = _get_peak(data, times, mode='abs')
assert_equal(ch_idx, 1)
assert_equal(time_idx, 1)
assert_allclose(max_amp, -3.)
ch_idx, time_idx, max_amp = _get_peak(data * -1, times, mode='neg')
assert_equal(ch_idx, 0)
assert_equal(time_idx, 2)
assert_allclose(max_amp, -2.)
ch_idx, time_idx, max_amp = _get_peak(data, times, mode='pos')
assert_equal(ch_idx, 0)
assert_equal(time_idx, 2)
assert_allclose(max_amp, 2.)
pytest.raises(ValueError, _get_peak, data + 1e3, times, mode='neg')
pytest.raises(ValueError, _get_peak, data - 1e3, times, mode='pos')
def test_get_peak():
"""Test peak getter."""
evoked = read_evokeds(fname, condition=0, proj=True)
assert_raises(ValueError, evoked.get_peak, ch_type='mag', tmin=1)
assert_raises(ValueError, evoked.get_peak, ch_type='mag', tmax=0.9)
assert_raises(ValueError, evoked.get_peak, ch_type='mag', tmin=0.02,
tmax=0.01)
assert_raises(ValueError, evoked.get_peak, ch_type='mag', mode='foo')
assert_raises(RuntimeError, evoked.get_peak, ch_type=None, mode='foo')
assert_raises(ValueError, evoked.get_peak, ch_type='misc', mode='foo')
ch_name, time_idx = evoked.get_peak(ch_type='mag')
assert_true(ch_name in evoked.ch_names)
assert_true(time_idx in evoked.times)
ch_name, time_idx, max_amp = evoked.get_peak(ch_type='mag',
time_as_index=True,
return_amplitude=True)
assert_true(time_idx < len(evoked.times))
assert_equal(ch_name, 'MEG 1421')
assert_allclose(max_amp, 7.17057e-13, rtol=1e-5)
assert_raises(ValueError, evoked.get_peak, ch_type='mag', merge_grads=True)
ch_name, time_idx = evoked.get_peak(ch_type='grad', merge_grads=True)
assert_equal(ch_name, 'MEG 244X')
data = np.array([[0., 1., 2.],
[0., -3., 0]])
times = np.array([.1, .2, .3])
ch_idx, time_idx, max_amp = _get_peak(data, times, mode='abs')
assert_equal(ch_idx, 1)
assert_equal(time_idx, 1)
assert_allclose(max_amp, -3.)
ch_idx, time_idx, max_amp = _get_peak(data * -1, times, mode='neg')
assert_equal(ch_idx, 0)
assert_equal(time_idx, 2)
assert_allclose(max_amp, -2.)
ch_idx, time_idx, max_amp = _get_peak(data, times, mode='pos')
assert_equal(ch_idx, 0)
assert_equal(time_idx, 2)
assert_allclose(max_amp, 2.)
assert_raises(ValueError, _get_peak, data + 1e3, times, mode='neg')
assert_raises(ValueError, _get_peak, data - 1e3, times, mode='pos')
def test_get_peak():
"""Test peak getter."""
evoked = read_evokeds(fname, condition=0, proj=True)
assert_raises(ValueError, evoked.get_peak, ch_type='mag', tmin=1)
assert_raises(ValueError, evoked.get_peak, ch_type='mag', tmax=0.9)
assert_raises(ValueError,
evoked.get_peak,
ch_type='mag',
tmin=0.02,
tmax=0.01)
assert_raises(ValueError, evoked.get_peak, ch_type='mag', mode='foo')
assert_raises(RuntimeError, evoked.get_peak, ch_type=None, mode='foo')
assert_raises(ValueError, evoked.get_peak, ch_type='misc', mode='foo')
ch_name, time_idx = evoked.get_peak(ch_type='mag')
assert_true(ch_name in evoked.ch_names)
assert_true(time_idx in evoked.times)
ch_name, time_idx = evoked.get_peak(ch_type='mag', time_as_index=True)
assert_true(time_idx < len(evoked.times))
assert_equal(ch_name, 'MEG 1421')
assert_raises(ValueError, evoked.get_peak, ch_type='mag', merge_grads=True)
ch_name, time_idx = evoked.get_peak(ch_type='grad', merge_grads=True)
assert_equal(ch_name, 'MEG 244X')
data = np.array([[0., 1., 2.], [0., -3., 0]])
times = np.array([.1, .2, .3])
ch_idx, time_idx = _get_peak(data, times, mode='abs')
assert_equal(ch_idx, 1)
assert_equal(time_idx, 1)
ch_idx, time_idx = _get_peak(data * -1, times, mode='neg')
assert_equal(ch_idx, 0)
assert_equal(time_idx, 2)
ch_idx, time_idx = _get_peak(data, times, mode='pos')
assert_equal(ch_idx, 0)
assert_equal(time_idx, 2)
assert_raises(ValueError, _get_peak, data + 1e3, times, mode='neg')
assert_raises(ValueError, _get_peak, data - 1e3, times, mode='pos')
def test_get_peak():
"""Test peak getter
"""
evoked = read_evokeds(fname, condition=0, proj=True)
assert_raises(ValueError, evoked.get_peak, ch_type='mag', tmin=1)
assert_raises(ValueError, evoked.get_peak, ch_type='mag', tmax=0.9)
assert_raises(ValueError, evoked.get_peak, ch_type='mag', tmin=0.02,
tmax=0.01)
assert_raises(ValueError, evoked.get_peak, ch_type='mag', mode='foo')
assert_raises(RuntimeError, evoked.get_peak, ch_type=None, mode='foo')
assert_raises(ValueError, evoked.get_peak, ch_type='misc', mode='foo')
ch_name, time_idx = evoked.get_peak(ch_type='mag')
assert_true(ch_name in evoked.ch_names)
assert_true(time_idx in evoked.times)
ch_name, time_idx = evoked.get_peak(ch_type='mag',
time_as_index=True)
assert_true(time_idx < len(evoked.times))
assert_equal(ch_name, 'MEG 1421')
data = np.array([[0., 1., 2.],
[0., -3., 0]])
times = np.array([.1, .2, .3])
ch_idx, time_idx = _get_peak(data, times, mode='abs')
assert_equal(ch_idx, 1)
assert_equal(time_idx, 1)
ch_idx, time_idx = _get_peak(data * -1, times, mode='neg')
assert_equal(ch_idx, 0)
assert_equal(time_idx, 2)
ch_idx, time_idx = _get_peak(data, times, mode='pos')
assert_equal(ch_idx, 0)
assert_equal(time_idx, 2)
assert_raises(ValueError, _get_peak, data + 1e3, times, mode='neg')
assert_raises(ValueError, _get_peak, data - 1e3, times, mode='pos')
def test_get_peak():
"""Test peak getter."""
evoked = read_evokeds(fname, condition=0, proj=True)
with pytest.raises(ValueError, match='tmin.*must be <= tmax'):
evoked.get_peak(ch_type='mag', tmin=1)
with pytest.raises(ValueError, match='tmax.*is out of bounds'):
evoked.get_peak(ch_type='mag', tmax=0.9)
with pytest.raises(ValueError, match='tmin.*must be <= tmax'):
evoked.get_peak(ch_type='mag', tmin=0.02, tmax=0.01)
with pytest.raises(ValueError, match="Invalid.*'mode' parameter"):
evoked.get_peak(ch_type='mag', mode='foo')
with pytest.raises(RuntimeError, match='Multiple data channel types'):
evoked.get_peak(ch_type=None, mode='foo')
with pytest.raises(ValueError, match='Channel type.*not found'):
evoked.get_peak(ch_type='misc', mode='foo')
ch_name, time_idx = evoked.get_peak(ch_type='mag')
assert (ch_name in evoked.ch_names)
assert (time_idx in evoked.times)
ch_name, time_idx, max_amp = evoked.get_peak(ch_type='mag',
time_as_index=True,
return_amplitude=True)
assert (time_idx < len(evoked.times))
assert_equal(ch_name, 'MEG 1421')
assert_allclose(max_amp, 7.17057e-13, rtol=1e-5)
with pytest.raises(ValueError, match='must be "grad" for merge_grads'):
evoked.get_peak(ch_type='mag', merge_grads=True)
with pytest.raises(ValueError, match='Negative mode.*does not make sense'):
evoked.get_peak(ch_type='grad', merge_grads=True, mode='neg')
ch_name, time_idx = evoked.get_peak(ch_type='grad', merge_grads=True)
assert_equal(ch_name, 'MEG 244X')
data = np.array([[0., 1., 2.], [0., -3., 0]])
times = np.array([.1, .2, .3])
ch_idx, time_idx, max_amp = _get_peak(data, times, mode='abs')
assert_equal(ch_idx, 1)
assert_equal(time_idx, 1)
assert_allclose(max_amp, -3.)
ch_idx, time_idx, max_amp = _get_peak(data * -1, times, mode='neg')
assert_equal(ch_idx, 0)
assert_equal(time_idx, 2)
assert_allclose(max_amp, -2.)
ch_idx, time_idx, max_amp = _get_peak(data, times, mode='pos')
assert_equal(ch_idx, 0)
assert_equal(time_idx, 2)
assert_allclose(max_amp, 2.)
# Check behavior if `mode` doesn't match the available data
evoked_all_pos = evoked.copy().crop(0, 0.1).pick('EEG 001')
evoked_all_neg = evoked.copy().crop(0, 0.1).pick('EEG 001')
evoked_all_pos.data = np.abs(evoked_all_pos.data) # all values positive
evoked_all_neg.data = -np.abs(evoked_all_neg.data) # all negative
with pytest.raises(ValueError, match='No negative values'):
evoked_all_pos.get_peak(mode='neg')
with pytest.raises(ValueError, match='No positive values'):
evoked_all_neg.get_peak(mode='pos')
# Test interaction between `mode` and `tmin` / `tmax`
# For the test, create an Evoked where half of the values are negative
# and the rest is positive
evoked_neg_and_pos = evoked_all_neg.copy()
time_sep_neg_and_pos = 0.05
idx_time_sep_neg_and_pos = evoked_neg_and_pos.time_as_index(
time_sep_neg_and_pos)[0]
evoked_neg_and_pos.data[:, idx_time_sep_neg_and_pos:] *= -1
with pytest.raises(ValueError, match='No positive values'):
evoked_neg_and_pos.get_peak(
mode='pos',
# subtract 1 time instant, otherwise were off-by-one
tmax=time_sep_neg_and_pos - 1 / evoked_neg_and_pos.info['sfreq'])
with pytest.raises(ValueError, match='No negative values'):
evoked_neg_and_pos.get_peak(mode='neg', tmin=time_sep_neg_and_pos)
selection = ['Gradiometers']
this_data = zscore_data(this_data, times)
# Get from evokeds dependent measures (peak latency, AUC) as ndarrays
for ii, _ in enumerate(groups):
for ci, _ in enumerate(conditions):
if n_sel > 1:
for jj in np.arange(n_sel):
for kk in np.arange(n_samples):
if ii == 0 and ci == 0 and jj == 0 and kk == 0:
# grp x cond x sel x subj
latencies = np.zeros(data.shape[:chs_dim])
locs = np.zeros_like(latencies)
amps = np.zeros_like(latencies) # AUC -100 ms to peak
out = _get_peak(data[ii, ci, jj, kk],
times,
tmin=.15,
tmax=.55)
locs[ii, ci, jj, kk] = out[0]
latencies[ii, ci, jj, kk] = out[1] # milliseconds
amps[ii, ci, jj, kk] = out[2]
b = np.where(np.isclose(times, out[1] * 1e-3,
atol=1e-3))[0][0]
a = np.where(
np.isclose(times, (out[1] - 100) * 1e-3,
atol=1e-3))[0][0]
auc = (np.sum(np.abs(data[ii, ci, jj, kk, :, a:b])) *
(len(times) / sfreq))
amps[ii, ci, jj, kk] = auc
# plot dependents
box_kwargs = {'showmeans': True, 'meanline': False}
condition='standard',
baseline=(None, 0))
standards.append(standard)
assert sfreq == standard.info['sfreq']
if group == groups[0] and subj == subjects[0]:
amp_data = np.zeros((len(groups), N))
lat_data = np.zeros((len(groups), N))
standard_data = np.zeros((len(groups), N))
# area under curve
tmin, tmax = (timing[ii] - .05, timing[ii])
mask = _time_mask(deviant.times, tmin=tmin, tmax=tmax, sfreq=sfreq)
dummy = deviant.copy().pick_channels(pairs[ii])
amp_data[ii, si] = np.sum(np.abs(dummy.data[:, mask])) * \
len(dummy.data) * (1. / sfreq)
lat_data[ii, si] = times[_get_peak(dummy.data,
times,
tmin=tmin,
tmax=tmax)[1]]
print(" Peak latency for %s at %.3f sec \n \n" %
(subj, lat_data[ii, si]))
del dummy
# for the standard stimulus
dummy = standard.copy().pick_channels(pairs[ii])
standard_data[ii, si] = np.sum(np.abs(deviant.data[:, mask])) * \
len(deviant.data) * (1. / deviant.info['sfreq'])
del dummy
for cond, evs, f in zip(conditions, [standards, deviants], f_out):
if not op.isfile(f):
grand_avr = grand_average(evs)
grand_avr.save(
op.join(
studydir, '%s_%s_%d_n%d_grand-ave.fif' %
